/*

Copyright (C) 1997,1998,1999,2000,2001  Franz Josef Och

mkcls - a program for making word classes .

This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation; either version 2
of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307,
USA.

*/




#include "RRTOptimization.h"
#include "ProblemTest.h"

double RRTOptimization::defaultAnnRate=0.6;
double RRTOptimization::defaultMultiple=2.0;



RRTOptimization::RRTOptimization(Problem &p,double t,double dt,int m)
  : IterOptimization(p,m),deviation(t),deltaDeviation(dt)
{
  assert(deviation>=0);
}



RRTOptimization:: RRTOptimization(Problem &p,int m)
  : IterOptimization(p,m),deviation(-1),deltaDeviation(0)
{
}



RRTOptimization::RRTOptimization(RRTOptimization &o)
  : IterOptimization(o)
{
  deviation     = o.deviation;
  deltaDeviation= o.deltaDeviation;
  record        = o.record;
}



void RRTOptimization::zInitialize()
{
  IterOptimization::zInitialize();
  if( deviation<0 ) {


    int n;

    StatVar &v=problem.deviationStatVar(*this,ANZ_VERSCHLECHTERUNGEN);

    if( maxStep>0 )
      n=(int)(maxStep*4.0/5.0);
    else
      maxStep=n=(int)(problem.expectedNumberOfIterations()*defaultMultiple);

    deviation      = v.quantil(defaultAnnRate);
    deltaDeviation = deviation/(float)n;

    if( verboseMode>0 )
      cout << "#Algorithm: Record-To-Record-Travel: (anfAnnRate="
           << defaultAnnRate << ",T=" << deviation << ",deltaT="
           << deltaDeviation << ")\n";

    curStep=0;
    endFlag=0;
    delete &v;
    problem.initialize();
    IterOptimization::zInitialize();
  }
  record=problem.value();
  assert(deviation>=0);
}

short RRTOptimization::end()
{
  return ( endFlag>0 && deviation==0.0 );
}
void  RRTOptimization::abkuehlen()
{
  if( deviation>=0 ) {
    deviation -= deltaDeviation;
    if(deviation<0)
      deviation=0;
  }
}
short RRTOptimization::accept(double delta)
{
  if( deviation<0 )
    return 1;
  else {
    if(  delta + curValue - deviation < record ) {
      if( delta + curValue < record )
        record = delta+curValue;
      return 1;
    } else
      return 0;
  }
}

void RRTOptimization::makeGraphOutput()
{
  IterOptimization::makeGraphOutput();
  *GraphOutput << deviation;
}




double RRTOptimization::optimizeValue(Problem &p,int proParameter,int numParameter,int typ,
                                      int optimierungsschritte,int print)
{
  switch(typ) {
  case 1: {
    double bestPar=-1,best=1e100;
    if( print )
      cout << "#RRT-optimizeValues: Quantil: " << numParameter << endl;
    for(int i=0; i<=numParameter; i++) {
      StatVar end,laufzeit,init;
      double now;
      if(i==0) defaultAnnRate=0.2;
      else defaultAnnRate = 0.3+(float)(0.6*i)/numParameter;
      solveProblem(0,p,proParameter,optimierungsschritte,RRT_OPT,now,
                   end,laufzeit,init);
      if( best>now ) {
        best=now;
        bestPar=defaultAnnRate;
      }
      if( print ) {
        cout << defaultAnnRate << " ";
        cout << end.getMean() << " " << end.quantil(0.2) << " "
             << end.quantil(0.79) << "  " << laufzeit.getMean() << " "
             << end.quantil(0.0) << " " << end.getSigma() << " "
             << end.getSigmaSmaller() << " " << end.getSigmaBigger()
             << " " << now << endl;
      }
    }
    if( print )
      cout << "#Parameter Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit "
           "Bester Sigma SigmaSmaller SigmaBigger\n";
    defaultAnnRate=0.8;
    return bestPar;
  }
  break;
  case 10: {
    double i;
    double bestPar=-1,best=1e100;
    StatVar end,laufzeit,init;

    if( print )
      cout << "#RRT-optimizeValues: defaultMultiple" << 8 << endl;
    for(i=0.5; i<=10; i+=1.5) {
      double now;
      defaultMultiple = i;
      solveProblem(0,p,proParameter,optimierungsschritte,RRT_OPT,now,
                   end,laufzeit,init);
      if( best>now ) {
        best=now;
        bestPar=defaultMultiple;
      }
      if( print ) {
        cout << defaultMultiple << " ";
        cout << end.getMean() << " " << end.quantil(0.2) << " "
             << end.quantil(0.79) << "  " << laufzeit.getMean() << " "
             << end.quantil(0.0) << " " << end.getSigma() << " "
             << end.getSigmaSmaller() << " " << end.getSigmaBigger()
             << " " << now << endl;
      }
    }
    if( print )
      cout << "#Parameter Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit "
           "Bester Sigma SigmaSmaller SigmaBigger\n";
    defaultMultiple=2.0;
    return bestPar;
  }
  break;
  default:
    cerr << "Error: wrong parameter-type in RRTOptimization::optimizeValue ("
         << typ << ")\n";
    exit(1);
  }
  return 1e100;
}


